This work presented a defect classification methods based on improved classification algorithm in additive manufacturing process. To make the algorithm be applicable in process monitoring tasks, a method of optimizing the evolution process in GP evolution was raised in this work. A series of specific functions and their linear combinations were introduced to represent the GP classification model. The evolution process in this strategy is designed to optimize the coefficients of these functions and the offset. The advantaged in GP are also completely inherited. Comparing with GP alone, the improved strategy could reach higher classification accuracy in engineering application, i.e., process monitoring of additive manufacture.
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
Tel.: +1 703 830 6300
Fax: +1 703 830 2300 email@example.com
(Corporate matters and books only) IOS Press c/o Accucoms US, Inc.
For North America Sales and Customer Service
West Point Commons
Lansdale PA 19446
Tel.: +1 866 855 8967
Fax: +1 215 660 5042 firstname.lastname@example.org